Learning from Conformance Quality Failures That Triggered Product Recalls: The Role of Direct and Indirect Experience

Abstract

A product recall is an observable external quality failure and a source of significant potential loss to firms as well as a threat to public safety. While such failures can be a motivation for organizational learning, little is known about the extent to which recalls can be a source of learning experience. Using econometric modeling, we investigate to what extent firms learn from conformance quality failures using a panel sample of U.S. food product recalls conducted by 125 publically traded firms between 2004 and 2013. We differentiate between direct (i.e., internal locus of failure) and indirect (i.e., supplier locus of failure and industry recalls) sources of experience and examine the main and interaction effects on the likelihood of future recalls. The results indicate that experience derived from internal and supplier failures reduces the potential for future recalls, while industry recalls have no significant main effect. We also find evidence of substitution effects between internal and supplier failures, suggesting that there are diminishing learning effects at higher levels of both of these types of failures. This finding suggests that the variety and volume of information as well as uncertainty regarding outcomes can overwhelm firm information processing capabilities at higher levels of these failure types and that additional resources should be allocated to encourage adequate learning. Finally, internal failures and industry recalls act as learning complements, which may indicate that internal quality failures become more relevant when industry peers also experience quality failures.

Supply chain disruptions: the influence of industry and geography on firm reaction speed

“…In particular, prior experience in undertaking recalls appears to transfer to new recall situations, enabling the firm to more rapidly respond to a supplier's recall. This is in line with prior work by Thirumalai and Sinha (2011) and Hall and Johnson-Hall (2017) suggesting that prior recalls also reduce the likelihood of future recalls. Future research could explore how the organization's learning regarding these unpredictable contingencies becomes codified so as to enhance future responsiveness.…”

Ramp Up and Ramp Down Dynamics in Digital Services

“…As projects get more complicated, managers stop learning from their experience and fall into an “experience trap” using simplified heuristics developed from earlier, simpler contexts (Sengupta, Abdel‐Habid & van Wassenhove, ). Hall and Johnson‐Hall () argue that in product recall, the learning derived from failures can reduce the potential for future recalls. We would expect a similar pattern in ramp downs.…”

“…There are growing numbers of recalls, particularly in products such as automotive and pharmaceutical where defective products have the potential to cause harm (Ball, Shah & Donohue, 2018;Hora, Bapuji & Roth, 2011). Causes of the need to recall can include design defects, manufacturing defects, inadequate testing, or inadequate or misleading instructions for use (Hall & Johnson-Hall, 2017;Hora et al, 2011). Of concern in product recalls is the time taken to recall (Ni & Huang, 2017).…”

Supply chain in the C-suite: the effect of chief supply chain officers on incidence of product recalls

“…While most recalls are not a consequence of such tragic outcomes, cases involving fatalities such as Mattel's sleepers, Takata's airbags (Chillingworth, 2020), Toyota's accelerators (Douglas and Fletcher, 2014) or Ikea's dressers (Kerley et al, 2016) have heightened interest amongst operations and supply chain management scholars and society at large in the drivers of product recalls. Not surprisingly, then, an increasing number of recent studies have investigated the underlying causes (Steven et al, 2014;Hall and Johnson-Hall, 2017;Shah et al, 2017;Ball et al, 2018).…”

“…There is widespread evidence of a steady increase in the incidence of recalls over the past decade (Cowley, 2016;Eshkenazi, 2016;Lucas, 2018;Ducharme, 2019) across multiple product categories and industrial sectors that include automotive (Shah et al, 2017); pharmaceutical (Ball et al, 2018); medical devices (Thirumalai and Sinha, 2011); toys (Hora et al, 2011); and food products (Hall and Johnson-Hall, 2017). In light of the costly and potentially dangerous repercussions for consumers and firms alike, this phenomenon warrants further investigation.…”